Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "200"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 200 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 55 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 53 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 200, Node N18:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459870 RF_maintenance 100.00% 100.00% 42.64% 0.00% - - 25.802367 69.173484 19.191046 18.757081 10.511671 17.296086 4.632672 0.614260 0.0477 0.2183 0.1434 nan nan
2459869 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2459868 RF_maintenance 100.00% 100.00% 74.38% 0.00% - - 23.537277 63.230600 28.252874 29.551919 10.704571 14.651193 5.037306 12.687675 0.0479 0.1912 0.1198 nan nan
2459867 RF_maintenance 100.00% 100.00% 59.08% 0.00% - - 16.432612 46.141239 21.843513 23.360242 5.684970 9.838308 3.350580 12.874569 0.0473 0.2029 0.1322 nan nan
2459866 RF_maintenance 100.00% 100.00% 55.96% 0.00% - - 18.951152 51.502248 21.023741 21.382744 6.183698 11.158294 1.094889 5.395369 0.0513 0.2075 0.1313 nan nan
2459865 RF_maintenance 100.00% 100.00% 54.51% 0.00% - - 21.062411 58.669921 23.397008 28.492759 15.471161 19.712014 15.118092 16.639725 0.0451 0.2236 0.1405 nan nan
2459864 RF_maintenance 100.00% 100.00% 73.79% 0.00% - - 25.507938 71.226652 7.511135 13.500627 8.122205 10.974662 5.375575 27.606754 0.0465 0.1924 0.1295 nan nan
2459863 RF_maintenance 100.00% 100.00% 69.07% 0.00% - - 15.490109 46.404152 2.423006 0.876265 2.912886 6.158194 2.485027 13.704268 0.0467 0.1984 0.1304 nan nan
2459862 RF_maintenance 100.00% 100.00% 67.52% 0.00% - - 15.363819 49.723736 8.122559 16.096472 12.486635 18.591203 1.810810 7.772214 0.0492 0.1988 0.1215 nan nan
2459861 RF_maintenance 100.00% 100.00% 68.64% 0.00% - - 11.802616 35.123671 2.687213 -0.182523 2.499090 2.793679 1.984077 9.980680 0.0465 0.1965 0.1160 nan nan
2459860 RF_maintenance 100.00% 100.00% 57.04% 0.00% - - 12.811866 36.233776 7.908440 12.745242 14.554448 16.236271 1.981036 5.325468 0.0458 0.2028 0.1341 nan nan
2459859 RF_maintenance 100.00% 100.00% 44.68% 0.00% - - 10.733740 32.545831 3.151592 -0.172601 2.148930 2.173343 0.920736 2.627577 0.0482 0.2106 0.1377 nan nan
2459858 RF_maintenance 100.00% 100.00% 95.11% 0.00% 100.00% 0.00% 11.677385 34.724317 3.163283 -0.482674 2.185114 3.410037 1.970158 7.542657 0.0479 0.2038 0.1332 1.265237 1.987776
2459857 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 5.046590 4.074326 0.582308 2.662401 2.083613 -0.461563 4.960186 6.433571 0.0668 0.0423 0.0215 nan nan
2459856 RF_maintenance 100.00% 100.00% 99.43% 0.00% 100.00% 0.00% 17.307219 49.628673 7.796184 11.550974 6.446090 11.190583 2.620625 -1.809000 0.0480 0.2006 0.1339 1.212078 1.583630
2459855 RF_maintenance 100.00% 100.00% 97.32% 0.00% 100.00% 0.00% 18.219379 55.090675 7.209504 13.434380 2.809717 6.060465 1.064928 -1.114998 0.0485 0.2160 0.1482 1.189857 1.511832
2459854 RF_maintenance 100.00% 100.00% 94.00% 0.00% 100.00% 0.00% 18.256309 55.377525 5.169951 11.727445 4.013889 5.598671 4.390431 0.949686 0.0498 0.2366 0.1673 1.204393 1.508662
2459853 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 15.121084 41.119658 7.838391 14.531188 6.832286 9.295279 3.147642 -1.398086 0.0504 0.2079 0.1349 1.224642 1.640459
2459852 RF_maintenance 100.00% 100.00% 55.68% 0.00% 100.00% 0.00% 13.721196 42.676192 8.503694 13.325663 15.481006 15.505904 16.811791 14.270269 0.0458 0.4044 0.3168 1.205998 2.001778
2459851 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000
2459850 RF_maintenance 100.00% 100.00% 82.94% 0.00% 100.00% 0.00% 14.468261 46.833015 6.900012 13.096907 10.212518 20.154058 6.489883 7.813720 0.0489 0.3204 0.2208 1.213461 1.558048
2459849 RF_maintenance 100.00% 100.00% 84.68% 0.00% 100.00% 0.00% 16.792554 48.454147 15.330846 26.898059 7.011023 13.551986 3.477155 0.870312 0.0488 0.2980 0.2032 1.226015 1.592434
2459848 RF_maintenance 100.00% 100.00% 83.79% 0.00% 100.00% 0.00% 15.467711 44.575018 7.769536 19.075644 14.294638 22.875158 1.632348 0.204478 0.0487 0.2934 0.2022 1.199897 1.497481
2459847 RF_maintenance 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 17.692049 46.477765 6.941161 18.217546 21.969969 16.764847 0.405474 -0.581668 0.0460 0.1924 0.1236 1.208910 1.564897
2459841 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 200: 2459870

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 69.173484 25.802367 69.173484 19.191046 18.757081 10.511671 17.296086 4.632672 0.614260

Antenna 200: 2459869

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance ee Shape nan nan nan inf inf nan nan nan nan

Antenna 200: 2459868

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 63.230600 23.537277 63.230600 28.252874 29.551919 10.704571 14.651193 5.037306 12.687675

Antenna 200: 2459867

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 46.141239 16.432612 46.141239 21.843513 23.360242 5.684970 9.838308 3.350580 12.874569

Antenna 200: 2459866

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 51.502248 51.502248 18.951152 21.382744 21.023741 11.158294 6.183698 5.395369 1.094889

Antenna 200: 2459865

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 58.669921 21.062411 58.669921 23.397008 28.492759 15.471161 19.712014 15.118092 16.639725

Antenna 200: 2459864

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 71.226652 71.226652 25.507938 13.500627 7.511135 10.974662 8.122205 27.606754 5.375575

Antenna 200: 2459863

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 46.404152 15.490109 46.404152 2.423006 0.876265 2.912886 6.158194 2.485027 13.704268

Antenna 200: 2459862

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 49.723736 15.363819 49.723736 8.122559 16.096472 12.486635 18.591203 1.810810 7.772214

Antenna 200: 2459861

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 35.123671 35.123671 11.802616 -0.182523 2.687213 2.793679 2.499090 9.980680 1.984077

Antenna 200: 2459860

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 36.233776 12.811866 36.233776 7.908440 12.745242 14.554448 16.236271 1.981036 5.325468

Antenna 200: 2459859

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 32.545831 10.733740 32.545831 3.151592 -0.172601 2.148930 2.173343 0.920736 2.627577

Antenna 200: 2459858

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 34.724317 34.724317 11.677385 -0.482674 3.163283 3.410037 2.185114 7.542657 1.970158

Antenna 200: 2459857

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Temporal Discontinuties 6.433571 4.074326 5.046590 2.662401 0.582308 -0.461563 2.083613 6.433571 4.960186

Antenna 200: 2459856

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 49.628673 17.307219 49.628673 7.796184 11.550974 6.446090 11.190583 2.620625 -1.809000

Antenna 200: 2459855

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 55.090675 55.090675 18.219379 13.434380 7.209504 6.060465 2.809717 -1.114998 1.064928

Antenna 200: 2459854

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 55.377525 55.377525 18.256309 11.727445 5.169951 5.598671 4.013889 0.949686 4.390431

Antenna 200: 2459853

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 41.119658 41.119658 15.121084 14.531188 7.838391 9.295279 6.832286 -1.398086 3.147642

Antenna 200: 2459852

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 42.676192 13.721196 42.676192 8.503694 13.325663 15.481006 15.505904 16.811791 14.270269

Antenna 200: 2459851

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance ee Shape nan nan nan inf inf nan nan nan nan

Antenna 200: 2459850

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 46.833015 14.468261 46.833015 6.900012 13.096907 10.212518 20.154058 6.489883 7.813720

Antenna 200: 2459849

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 48.454147 16.792554 48.454147 15.330846 26.898059 7.011023 13.551986 3.477155 0.870312

Antenna 200: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 44.575018 44.575018 15.467711 19.075644 7.769536 22.875158 14.294638 0.204478 1.632348

Antenna 200: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance nn Shape 46.477765 46.477765 17.692049 18.217546 6.941161 16.764847 21.969969 -0.581668 0.405474

Antenna 200: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
200 N18 RF_maintenance ee Shape nan nan nan inf inf nan nan nan nan
In [ ]: